Tree diversity increases productivity through enhancing structural complexity across mycorrhizal types

Tree species diversity and mycorrhizal associations play a central role for forest productivity, but factors driving positive biodiversity-productivity relationships remain poorly understood. In a biodiversity experiment manipulating tree diversity and mycorrhizal associations, we examined the roles of above- and belowground processes in modulating wood productivity in young temperate tree communities and potential underlying mechanisms. We found that tree species richness, but not mycorrhizal associations, increased forest productivity by enhancing aboveground structural complexity within communities. Structurally complex communities were almost twice as productive as structurally simple stands, particularly when light interception was high. We further demonstrate that overyielding was largely explained by positive net biodiversity effects on structural complexity with functional variation in shade tolerance and taxonomic diversity being key drivers of structural complexity in mixtures. Consideration of stand structural complexity appears to be a crucial element in predicting carbon sequestration in the early successional stages of mixed-species forests.

Table S1.Results of linear mixed-effects models of the effects of tree species richness on stand structural complexity (SSCI) and community productivity (AWP).SD, standard deviation.The variance explained by the fixed effects alone (marginal R 2 ) and by both the fixed and random effects (conditional R 2 ) was calculated according to (80).See Table 1       factor with two levels.There was no interaction between tree species richness and shade tolerance (P = 0.377), but shade tolerance had a strong negative effect on tree height (P = 0.0008).Across all species included in our experiment, tree species richness did not affect tree height (P = 0.441).

Fig. S1 .
Fig. S1.Effect sizes for the biodiversity-complexity relationship showing how tree species richness affects the strength of biodiversity effects (Hedges' g effect size) on stand structural complexity (SSCI).Points are predicted means of mixed-effects models, and error bars denote the 95% confidence intervals.Positive values indicate a higher structural complexity in mixed-species communities compared to monocultures, while negative values indicate the opposite.Error bars not overlapping with zero indicate significant biodiversity effects, and vice versa.Across mixtures: 2-and 4-species mixtures.

Fig. S2 .
Fig. S2.Effects of mycorrhizal associations on community productivity does not depend on tree species richness.Boxplots show the median (horizontal white lines), the 25% and 75% percentiles (edges of the box) and 1.5 times the interquartile range (whiskers) of observed community productivity.Open circles indicate productivity values that are greater or smaller than 1.5 times the interquartile range.Differences among mycorrhizal associations were not statistically significant (Tukey-Test: P > 0.10).Note that the interaction between tree species richness and mycorrhizal associations was not significant (P = 0.54).AM: arbuscular mycorrhizal tree species; EM: ectomycorrhizal tree species.

Fig. S4 .
Fig. S4.Shade tolerance-structural complexity relationship.Relationship between the net effect of tree species richness on structural complexity (ΔSSCI) and the functional dispersion (FD) of shade tolerance within mixtures.For each mixture, ΔSSCI was calculated as the difference between observed (SSCIobs) and predicted (SSCIpred) structural complexity (see Methods).The solid line is a mixed-effect model fit.The dotted lines indicate the 95% confidence interval of the prediction.Raw data are shown with individual data points, with triangles showing plots containing both Betula pendula and Fagus sylvatica growing in 2-species (light green) or 4-species (dark green) mixtures.The R²-value refers to the proportion of variance explained by FD.

Fig. S5 .
Fig. S5.Light condition-structural complexity relationship.Correlation between the mean light intensity at ground level (used as a proxy for stand-level light interception), and stand structural complexity (SSCI) for a subset of plots (n=40).The solid line is a linear model fit, and the shaded area indicates the 95% confidence interval of the prediction.Raw data are shown with individual data points.Different colors indicate tree species richness levels and different shapes correspond to mycorrhizal associations.

Fig. S6 .
Fig. S6.Effects of shade tolerance on tree height growth in mixed-species tree communities.Univariate relationships are displayed for 2-species mixtures and 4-species mixtures.Individual dots represent the average height in 2021 (year of scanning) of a species in a plot.Lines are generalized linear model fits (Gamma distribution and log link function).Shade tolerance was used as a continuous variable in the model, while species richness was used as a

Fig. S7 .
Fig. S7.Graphical representation of tree species diversity effects on stand productivity, enhanced by stand structural complexity.Greater tree species richness allows different species to grow in different strata depending on their degree of morphological, architectural and functional dissimilarity.This promotes greater vertical stratification (ENL) and 3-dimensional heterogeneity in biomass distribution (MeanFrac) of the stand, two basic components of stand structural complexity.Therefore, we hypothesized that the structural complexity of a tree community enhances resource acquisition of the trees and helps to store wood biomass in different strata of the stand.

Table S2 . List of tree species used in the MyDiv experiment and their associated functional characteristics, including mycorrhizal associations, net primary productivity in monoculture and shade tolerance indices.
for further information.Within each category of tree species' preferred mycorrhizal association, species are ranked from most to least productive.AM, arbuscular mycorrhiza; EM, ectomycorrhiza; AWP, annual wood productivity.